The frequency table that corresponds to the line plot contains the same information, but it's in another form (or representation). Part of the lesson here is to understand that there can be more than one way to represent data and to see the connection between two representations. You will be asked to consider the same 10 questions as before. Though you already know the answers, by solving the problems again, you will learn how to use the table, and you can compare the experience of using the table with that of using the line plot.

Keep in mind that different people see ideas in different ways. Some prefer graphical representations, and some prefer tabular representations. Luckily, in statistics we use both.

The frequency table gave us the number of times a specific value occurred. We have also seen how an interval is used to describe how many raisins are in a box; for example, most of the boxes (14/17) contain between 26 and 29 raisins. We were able to determine how many of the counts fall in the interval 26-29 by adding the individual frequencies in this range.

The cumulative frequency function simplifies this process and gives us a more convenient device for obtaining frequencies for an interval of data; the cumulative frequency function has already done the adding! Keep in mind that with large data sets this would be an even greater advantage. If you have the cumulative frequencies, then the computation of the frequency within an interval is simply the difference between two numbers. This idea may not be obvious at first, but you'll see as you get to play with it a bit in this part of the session.

If you are working with actual raisins, make frequency and cumulative frequency tables with your own data.